If you want to do your own code from scratch, we'd love it: wherever you live, you can help make your local government more accessible. We're building a collection of web scrapers and data import scripts that turn a set of laws into JSON. Here's an example in Haskell, for the U.S. state of Nevada: github.com/public-law/nevada-revis.... But like I said, any language is great. It doesn't matter if you're a beginner or advanced. The most important thing is to get something that works for every place on earth. Since it'll run on Ubuntu and simply output JSON, anyone can use these data feeds to make innovative apps.

But if you just want to contribute a little bit of documentation, or maybe do some refactoring, we have a bunch of open source repo's already up.

Hey. I am absurdly good at scraping but like Hafidz don't get the bigger picture either.
Do you have any type of DTD? Specifics? Does it need to be parsed to useful format once (do you just want the data?) or is it expected to run periodically?
(Sources change and so the parser needs to change too)

Hi Robb, I am just one who keep looking any project updates in this post and just stop by yours. But to be honest, I am just dummy coder. Currently, I was interesting in building data pre-processing framework for web data, before they are inserted into database.

I have visited all your links, but I just can not catch the big picture, such as what kind of data need to be scrapped, output criteria, design rule, etc. Can you give me more information?

FYI: I am from Indonesia, so there are not many open data about law compared to USA.

Hey, we're working on xstate: github.com/davidkpiano/xstate - a library for declaratively making state machines and statecharts that not only reduces the complexity of your application behavior, but can also automatically generate tests and visualize app state!

It's currently being used in projects such as Gatsby, and workshop.me, and quite a few others! I'd love for people to help contribute documentation, as well as help to add features, fix bugs (there aren't many at all, actually), and create sample projects.

I'm excited about the future of this project because it has foundation in decades worth of software modeling research (statecharts were first introduced in 1987) and has applications in all types of projects, especially user interfaces. There's a huge potential for these ideas to greatly simplify application complexity in a robust, visual way.

If you're looking to make an impact in the Python ecosystem the urllib3 package has a list of outstanding issues marked as Contributor Friendly where maintainers are willing to spend extra time with new contributors and have relatively straightforward changes required in order to ease your way into a new complex codebase. Contributing to urllib3 has a huge impact to the Python ecosystem because it's depended on for some of it's most important modules (pip, requests, and boto3 to name a few!)

So, I have a slightly different angle on this question. While I am looking for folks who want to work on msngr.js (a messaging library for handling publish and subscriptions within JavaScript) I also am not sure where else to take it or if it's simply "done". I have some loyal users but they literally need no additional features or changes.

This is really interesting. I'ma check this out as well.
One thing though, don't use the word async as identifier like in your readme because it is a part of the JavaScript language these days.
But really, looks interesting.

I've been working on a pull request plugin for VIM: github.com/AGhost-7/critiq.vim. It does the job for me, but I'm sure there's quite a few features people would like added to it. Could really use some help since I'm not entirely familiar with the vim language.

I am working on a way to have commit conventions within projects, therefore I introduced semantic-git-commit-cli, in short sgc, which helps with that. github.com/JPeer264/node-semantic-...

I am also doing now on a research for a GitHub recommender for contributors. Would be neat if any can spare some time and fill in the form (pssst, you can win a 20€ Amazon Voucher Code): goo.gl/forms/ogC5oKJbfM5xhSzr2

With that recommender I want to achieve that you can find projects where you can contribute to next.

nx-build is a project file generator for C & C++, using Javascript as a scripting language. It's a project that I started quite recently so any contributions or tips/advice would be awesome. I'm also aiming to build up a common place that documents build programs and file formats so any help with that ambitious undertaking is welcome :D
I don't want to limit those docs to just C/C++, other language build tools are just as welcome, if not more :)

Languages/Frameworks:

Node.js (currently the original prototype is being rewritten in typescript)

I just dropped a release candidate for Massive v5: npm i massive@next to get it. If anyone's interested in taking a Node+Postgres data access library for a spin and reporting back I'd love to hear from you!

Hey! Just wanted to drop in and say thanks again. Sample Programs in Every Language has jumped from essentially nothing to 19 stars and 9 forks thanks to this weekly post. I appreciate the help as it allows me to focus on writing.

More often than not, testing software consumes a large portion of the development budget, however we frequently see cases where unit and integration tests fail to uncover critical errors that appear once the software is deployed. Most testing techniques revolve around specifying a collection of execution sequences that check the expected against the actual behavior. A problem with this is that the number of possible execution sequences is huge, and therefore only a very small portion of these would be covered by test cases that are specified as a sequence of steps. The second problem is that, with the goal of increasing coverage and prevent regression bugs a large number of test cases is written, which eats up the development budget.

Model-based testing is a technique for writing tests, where a model of the system behavior is made a a high-level of abstraction, and then the system-under test is tested against this the expected behavior as specified by the model. Model-based testing relies on different algorithms for generating test cases from models, which allows to achieve a much higher test coverage than standard testing techniques, while requiring only a fraction of the code.

TorXakis is such a model-based testing tool, that has been used to verify large scale systems in well-know high tech companies. This tool is entirely written in Haskell, and its code is available on Github under a BSD3 license.

Since July last year, a lot of effort was put into taking TorXakis from a prototype to an industrial grade tool. Some of the improvements made include: